Academic Commons Search Resultshttps://academiccommons.columbia.edu/catalog?action=index&controller=catalog&f%5Bsubject_facet%5D%5B%5D=Remote+sensing&format=rss&fq%5B%5D=has_model_ssim%3A%22info%3Afedora%2Fldpd%3AContentAggregator%22&q=&rows=500&sort=record_creation_date+desc
Academic Commons Search Resultsen-usEvidence and analysis of 2012 Greenland records from spaceborne observations, a regional climate model and reanalysis datahttps://academiccommons.columbia.edu/catalog/ac:196260
Tedesco, Marco; Fettweis, X.; Mote, T.; Wahr, J.; Alexander, P.; Box, J. E.; Wouters, B.http://dx.doi.org/10.7916/D8J38SGVWed, 30 Mar 2016 11:45:26 +0000A combined analysis of remote sensing observations, regional climate model (RCM) outputs and reanalysis data over the Greenland ice sheet provides evidence that multiple records were set during summer 2012. Melt extent was the largest in the satellite era (extending up to ∼97% of the ice sheet) and melting lasted up to ∼2 months longer than the 1979–2011 mean. Model results indicate that near surface temperature was ∼3 standard deviations (σ) above the 1958–2011 mean, while surface mass balance (SMB) was ∼3σ below the mean and runoff was 3.9σ above the mean over the same period. Albedo, exposure of bare ice and surface mass balance also set new records, as did the total mass balance with summer and annual mass changes of, respectively, −627 Gt and −574 Gt, 2σ below the 2003–2012 mean. We identify persistent anticyclonic conditions over Greenland associated with anomalies in the North Atlantic Oscillation (NAO), changes in surface conditions (e.g., albedo, surface temperature) and preconditioning of surface properties from recent extreme melting as major driving mechanisms for the 2012 records. Less positive if not increasingly negative SMB will likely occur should these characteristics persist.Geology, Geomorphology, Climate change, Remote sensing, Ice sheets, Ice sheets--Measurement, Meltwater, Climatic geomorphology, Geomorphologymt3102Lamont-Doherty Earth ObservatoryArticlesDefining and quantifying microscale wave breaking with infrared imageryhttps://academiccommons.columbia.edu/catalog/ac:195365
Jessup, A. T.; Zappa, Christopher J.; Yeh, Harryhttp://dx.doi.org/10.7916/D8GT5N29Mon, 07 Mar 2016 12:53:46 +0000Breaking without air entrainment of very short wind-forced waves, or microscale wave breaking, is undoubtedly widespread over the oceans and may prove to be a significant mechanism for enhancing the transfer of heat and gas across the air-sea interface. However, quantifying the effects of microscale wave breaking has been difficult because the phenomenon lacks the visible manifestation of whitecapping. In this brief report we present limited but promising laboratory measurements which show that microscale wave breaking associated with evolving wind waves disturbs the thermal boundary layer at the air-water interface, producing signatures that can be detected with infrared imagery. Simultaneous video and infrared observations show that the infrared signature itself may serve as a practical means of defining and characterizing the microscale breaking process. The infrared imagery is used to quantify microscale breaking waves in terms of the frequency of occurrence and the areal coverage, which is substantial under the moderate wind speed conditions investigated. The results imply that ”bursting“ phenomena observed beneath laboratory wind waves are likely produced by microscale breaking waves but that not all microscale breaking waves produce bursts. Oceanic measurements show the ability to quantify microscale wave breaking in the field. Our results demonstrate that infrared techniques can provide the information necessary to quantify the breaking process for inclusion in models of air-sea heat and gas fluxes, as well as unprecedented details on the origin and evolution of microscale wave breaking.Physical oceanography, Hydrologic sciences, Remote sensing, Ocean waves--Remote sensing, Infrared imaging, Wind waves--Measurementcjz9Lamont-Doherty Earth ObservatoryArticlesValidation of Long-Term Global Aerosol Climatology Project Optical Thickness Retrievals Using AERONET and MODIS Datahttps://academiccommons.columbia.edu/catalog/ac:194283
Geogdzhayev, Igor V.; Mishchenko, Michael I.http://dx.doi.org/10.7916/D8DJ5FGTMon, 15 Feb 2016 12:46:33 +0000A comprehensive set of monthly mean aerosol optical thickness (AOT) data from coastal and island AErosol RObotic NETwork (AERONET) stations is used to evaluate Global Aerosol Climatology Project (GACP) retrievals for the period 1995–2009 during which contemporaneous GACP and AERONET data were available. To put the GACP performance in broader perspective, we also compare AERONET and MODerate resolution Imaging Spectroradiometer (MODIS) Aqua level-2 data for 2003–2009 using the same methodology. We find that a large mismatch in geographic coverage exists between the satellite and ground-based datasets, with very limited AERONET coverage of open-ocean areas. This is especially true of GACP because of the smaller number of AERONET stations at the early stages of the network development. Monthly mean AOTs from the two over-the-ocean satellite datasets are well-correlated with the ground-based values, the correlation coefficients being 0.81–0.85 for GACP and 0.74–0.79 for MODIS. Regression analyses demonstrate that the GACP mean AOTs are approximately 17%–27% lower than the AERONET values on average, while the MODIS mean AOTs are 5%–25% higher. The regression coefficients are highly dependent on the weighting assumptions (e.g., on the measure of aerosol variability) as well as on the set of AERONET stations used for comparison. Comparison of over-the-land and over-the-ocean MODIS monthly mean AOTs in the vicinity of coastal AERONET stations reveals a significant bias. This may indicate that aerosol amounts in coastal locations can differ significantly from those in adjacent open-ocean areas. Furthermore, the color of coastal waters and peculiarities of coastline meteorological conditions may introduce biases in the GACP AOT retrievals. We conclude that the GACP and MODIS over-the-ocean retrieval algorithms show similar ranges of discrepancy when compared to available coastal and island AERONET stations. The factors mentioned above may limit the performance of the validation procedure and cause us to caution against a direct extrapolation of the presented validation results to the entirety of the GACP dataset.Remote sensing, Environmental science, Aeronomy, Tropospheric aerosols, Remote sensing, MODIS (Spectroradiometer)ig117Applied Physics and Applied MathematicsArticlesThe Impact of Deciduous Shrub Dominance on Phenology, Carbon Flux, and Arthropod Biomass in the Alaskan Arctic Tundrahttps://academiccommons.columbia.edu/catalog/ac:191050
Sweet, Shannan Kathlynhttp://dx.doi.org/10.7916/D8ZG6RV4Tue, 17 Nov 2015 10:30:29 +0000Arctic air temperatures have increased at two to three times the global rate over the past century. As a result, abiotic and biotic responses to climate change are more rapid and pronounced in the Arctic compared to other biomes. One important change detected over the past several decades by satellite studies is a lengthening of the arctic growing season, which is due to earlier onsets and/or delayed ends to growing seasons. A handful of studies also suggest the peak green season (i.e. when the tundra is at maximum leaf-out and maximum carbon uptake potential) is starting earlier in the arctic tundra. The vast majority of studies detecting shifts in the growing season suggest this is due to increasing spring and fall air temperatures, which lead to earlier spring snowmelt and later fall snowfall. Less well understood is how indirect consequences of arctic warming, such as ongoing changes in plant community composition, may also be contributing to these satellite signals. For instance, there is mounting evidence that deciduous shrubs are expanding into previously non-shrub dominated tundra in several parts of the Arctic. Deciduous shrubs may alter tundra canopy phenology and contribute to the regional shifts in timing of phenological events being detected by satellites.
Concurrently, in many areas where deciduous shrubs are expanding they are also becoming taller. As taller shrubs become increasingly dominant, arctic landscapes may retain more snow, which could lengthen spring snow cover duration, and offset advances in the start of the growing season that are expected as a result of earlier spring snowmelt. As a consequence, deeper snow and later snowmelt in taller shrub tundra could delay plant emergence, and shorten the period of annual carbon uptake. Thus greater dominance of taller stature deciduous shrubs in the Arctic may actually delay the onset of the growing season, which would suggest that increasing deciduous shrub dominance may not be contributing to satellite signals of an earlier start to the growing season. To contribute to satellite-detected shifts in the onset of the growing and peak seasons, tall deciduous shrubs would need to have accelerated leaf development to compensate for deeper snow packs and later spring snowmelt relative to surrounding tundra.
Understanding the drivers of shifts in tundra phenology is important since longer (or shorter) growing and peak green seasons would increase (or decrease) productivity and the period of carbon uptake, which will have implications for landscape-level carbon exchange, and ultimately global carbon balances.
Given the rate and magnitude of changes occurring in the face of acute arctic warming, there is a need to monitor, understand, and predict ecological responses over large spatial and temporal scales. However, compared to more southern environments, the arctic tundra is characterized by considerable heterogeneity in vegetation distribution, as well as a short and rapid growing season. In addition, the arctic tundra is relatively vast and inaccessible. These characteristics can make it difficult to monitor and study changes in the Arctic, and make it difficult to develop landscape-level models able to predict changes in ecosystem dynamics and tundra vegetation. The use of airborne and satellite sensors has at least partially fulfilled these needs to monitor, understand, and predict change in the Arctic. The normalized difference vegetation index (NDVI) acquired from these sensors, for instance, has become a widely adopted tool for detecting and quantifying spatial-temporal dynamics in tundra vegetation cover, productivity, and phenology. This suggests that remote sensing technology and vegetation indices may be similarly applied to characterizing patterns of primary and secondary consumers (e.g. arthropods), which would be enormously useful in a region as vast and remote as the Arctic.
The research presented in this dissertation provides useful insight into the influence vegetation community composition, particularly increasing deciduous shrub dominance, has on phenology, carbon flux, and canopy arthropod biomass in the arctic foothills region of the Brooks Range, Alaska. Findings in Chapter one suggest that delayed snowmelt in areas dominated by taller shrubs may have a short-lived impact on the timing of leaf development, likely resulting in no difference in duration of peak photosynthetic period between tall and short- stature shrubs. Findings in Chapter two suggest that greater deciduous shrub dominance not only increases carbon uptake due to higher leaf area relative to surrounding tundra, but may also be causing an earlier onset of, and ultimately a net extension of, the period of maximum tundra greenness and further increasing peak season carbon sequestration. Findings in Chapter three suggest that measurements of the NDVI made from air and spaceborne sensors may be able to quantify spatial and temporal variation in canopy arthropod biomass at landscape to regional scales in the arctic tundra.Climate change, Environmental studies, Remote sensing, Ecology, Plant phenology, Vegetation and climate, Climatic changes, Vegetation surveys--Remote sensingsks2171Earth and Environmental SciencesDissertationsMapping Species Composition of Forests and Tree Plantations in Northeastern Costa Rica with an Integration of Hyperspectral and Multitemporal Landsat Imageryhttps://academiccommons.columbia.edu/catalog/ac:189753
Fagan, Matthew E.; DeFries, Ruth S.; Sesnie, Steven E.; Arroyo-Mora, J. Pablo; Soto, Carlomagno; Singh, Aditya; Townsend, Philip A.; Chazdon, Robin L.http://dx.doi.org/10.7916/D8P55N15Thu, 15 Oct 2015 15:56:17 +0000An efficient means to map tree plantations is needed to detect tropical land use change and evaluate reforestation projects. To analyze recent tree plantation expansion in northeastern Costa Rica, we examined the potential of combining moderate-resolution hyperspectral imagery (2005 HyMap mosaic) with multitemporal, multispectral data (Landsat) to accurately classify (1) general forest types and (2) tree plantations by species composition. Following a linear discriminant analysis to reduce data dimensionality, we compared four Random Forest classification models: hyperspectral data (HD) alone; HD plus interannual spectral metrics; HD plus a multitemporal forest regrowth classification; and all three models combined. The fourth, combined model achieved overall accuracy of 88.5%. Adding multitemporal data significantly improved classification accuracy (p < 0.0001) of all forest types, although the effect on tree plantation accuracy was modest. The hyperspectral data alone classified six species of tree plantations with 75% to 93% producer’s accuracy; adding multitemporal spectral data increased accuracy only for two species with dense canopies. Non-native tree species had higher classification accuracy overall and made up the majority of tree plantations in this landscape. Our results indicate that combining occasionally acquired hyperspectral data with widely available multitemporal satellite imagery enhances mapping and monitoring of reforestation in tropical landscapes.Ecology, Remote sensing, Forestryrd2402Ecology, Evolution, and Environmental BiologyArticlesAutonomous Ocean Measurements in the California Current Ecosystemhttps://academiccommons.columbia.edu/catalog/ac:189286
Ohman, Mark D.; Rudnick, Daniel L.; Chekalyuk, Alexander M.; Davis, Russ E.; Feely, Richard A.; Kahru, Mati; Kim, Hey-Jin; Landry, Michael R.; Martz, Todd R.; Sabine, Christopher L.; Send, Uwehttp://dx.doi.org/10.7916/D80C4V7TFri, 09 Oct 2015 15:23:21 +0000Event-scale phenomena, of limited temporal duration or restricted spatial extent, often play a disproportionately large role in ecological processes occurring in the ocean water column. Nutrient and gas fluxes, upwelling and downwelling, transport of biogeochemically important elements, predator-prey interactions, and other processes may be markedly influenced by such events, which are inadequately resolved from infrequent ship surveys. The advent of autonomous instrumentation, including underwater gliders, profiling floats, surface drifters, enhanced moorings, coastal high-frequency radars, and satellite remote sensing, now provides the capability to resolve such phenomena and assess their role in structuring pelagic ecosystems. These methods are especially valuable when integrated together, and with shipboard calibration measurements and experimental programs.Ecology, Hydrologic sciences, Remote sensing, Geographic information science and geodesy, Biological oceanographyac2709Lamont-Doherty Earth ObservatoryArticlesGreater deciduous shrub abundance extends tundra peak season and increases modeled net CO₂ uptakehttps://academiccommons.columbia.edu/catalog/ac:191047
Sweet, Shannan Kathlyn; Griffin, Kevin L.; Steltzer, Heidi; Gough, Laura; Boelman, Natalie T.http://dx.doi.org/10.7916/D80Z72QKFri, 02 Oct 2015 14:33:06 +0000Satellite studies of the terrestrial Arctic report increased summer greening and longer overall growing and peak seasons since the 1980s, which increases productivity and the period of carbon uptake. These trends are attributed to increasing air temperatures and reduced snow cover duration in spring and fall. Concurrently, deciduous shrubs are becoming increasingly abundant in tundra landscapes, which may also impact canopy phenology and productivity. Our aim was to determine the influence of greater deciduous shrub abundance on tundra canopy phenology and subsequent impacts on net ecosystem carbon exchange (NEE) during the growing and peak seasons in the arctic foothills region of Alaska. We compared deciduous shrub-dominated and evergreen/graminoid-dominated community-level canopy phenology throughout the growing season using the normalized difference vegetation index (NDVI). We used a tundra plant-community-specific leaf area index (LAI) model to estimate LAI throughout the green season and a tundra-specific NEE model to estimate the impact of greater deciduous shrub abundance and associated shifts in both leaf area and canopy phenology on tundra carbon flux. We found that deciduous shrub canopies reached the onset of peak greenness 13 days earlier and the onset of senescence 3 days earlier compared to evergreen/graminoid canopies, resulting in a 10-day extension of the peak season. The combined effect of the longer peak season and greater leaf area of deciduous shrub canopies almost tripled the modeled net carbon uptake of deciduous shrub communities compared to evergreen/graminoid communities, while the longer peak season alone resulted in 84% greater carbon uptake in deciduous shrub communities. These results suggest that greater deciduous shrub abundance increases carbon uptake not only due to greater leaf area, but also due to an extension of the period of peak greenness, which extends the period of maximum carbon uptake.Ecology, Environmental science, Remote sensing, Plant phenology, Vegetation and climate, Carbon cycle, Vegetation surveys--Remote sensingsks2171, kg109, ntb12Earth and Environmental Sciences, Lamont-Doherty Earth ObservatoryArticlesCorrelation scales of digital elevation models in developed coastal environmentshttps://academiccommons.columbia.edu/catalog/ac:191958
Small, Christopher; Sohn, Roberthttp://dx.doi.org/10.7916/D8TQ60ZJThu, 01 Oct 2015 15:53:01 +0000Accuracy of digital elevation models (DEMs) often depends on how features of different spatial scales are represented. Scale dependence is particularly important in low gradient coastal environments where small vertical errors can affect large areas and where representation of fine scale topographic features can influence how DEMs are used for modeling inundation. It is commonly observed that different types of DEMs represent larger, coarse-scale topographic features similarly but differ in how they represent smaller, finer-scale features. The spatial-scale dependence of DEM accuracy can be quantified in terms of the correlation scale (λC); the spatial wavelength above which models agree with spectral coherency > 0.5 and below which they differ. We compare cross spectral analyses of the GDEM2 and SRTM global DEMs with 14,572 LiDAR-derived elevations along transects in diverse coastal environments of New York City. Both global DEMs have positive bias relative to LiDAR ground elevations, but bias (μ) and uncertainty (σ) of GDEM2 (μ: 8.1 m; σ: 7.6 m) are significantly greater than those of SRTM (μ: 1.9 m; σ: 3.6 m). Cross-spectral coherency between GDEM2 and the LiDAR DEM begins to roll-off at scales of λ < ~ 3 km, while coherency between SRTM and the LiDAR DEM begins to roll-off at scales of λ < ~ 1 km. The correlation scale below which coherency with LiDAR attains a signal to noise ratio of 1 is ~ 1 km for GDEM2 and ~ 0.5 km for SRTM; closely matching the divergence scales where the surface roughness of the land cover exceeds the roughness of the underlying terrain.Remote sensing, Geographic information science and geodesy, Geomorphology, Digital elevation models, Measurement, Altitudes, Coastscs184Lamont-Doherty Earth ObservatoryArticlesGlobal satellite monitoring of climate-induced vegetation disturbanceshttps://academiccommons.columbia.edu/catalog/ac:191570
McDowell, Nate G.; Coops, Nicholas C.; Beck, Pieter S. A.; Chambers, Jeffrey Q.; Gangodagamage, Chandana; Hicke, Jeffrey A.; Huang, Cho-ying; Kennedy, Robert; Krofcheck, Dan J.; Litvak, Marcy; Meddens, Arjan J. H.; Muss, Jordan; Peng, Changhui; Negrón-Juarez, Robinson; Schwantes, Amanda M.; Swenson, Jennifer J.; Vernon, Louis J.; Williams, A. Park; Zhao, Maosheng; Xu, Chonggang; Running, Steve W.; Allen, Craig D.http://dx.doi.org/10.7916/D8S46RCVWed, 30 Sep 2015 16:06:37 +0000Terrestrial disturbances are accelerating globally, but their full impact is not quantified because we lack an adequate monitoring system. Remote sensing offers a means to quantify the frequency and extent of disturbances globally. Here, we review the current application of remote sensing to this problem and offer a framework for more systematic analysis in the future. We recommend that any proposed monitoring system should not only detect disturbances, but also be able to: identify the proximate cause(s); integrate a range of spatial scales; and, ideally, incorporate process models to explain the observed patterns and predicted trends in the future. Significant remaining challenges are tied to the ecology of disturbances. To meet these challenges, more effort is required to incorporate ecological principles and understanding into the assessments of disturbance worldwide.Remote sensing, Ecology, Climate change, Vegetation monitoring--Remote sensing, Remote sensing, Ecologyapw2134Lamont-Doherty Earth ObservatoryArticlesMoist Static Energy Budget of the MJO during DYNAMOhttps://academiccommons.columbia.edu/catalog/ac:191146
Sobel, Adam H.; Wang, Shuguang; Kim, Daehyunhttp://dx.doi.org/10.7916/D8JS9PTCMon, 28 Sep 2015 15:47:04 +0000The authors analyze the column-integrated moist static energy budget over the region of the tropical Indian Ocean covered by the sounding array during the Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year 2011 (CINDY2011)/Dynamics of the Madden–Julian Oscillation (DYNAMO) field experiment in late 2011. The analysis is performed using data from the sounding array complemented by additional observational datasets for surface turbulent fluxes and atmospheric radiative heating. The entire analysis is repeated using the ECMWF Interim Re-Analysis (ERA-Interim). The roles of surface turbulent fluxes, radiative heating, and advection are quantified for the two MJO events that occurred in October and November using the sounding data; a third event in December is also studied in the ERA-Interim data.
These results are consistent with the view that the MJO’s moist static energy anomalies grow and are sustained to a significant extent by the radiative feedbacks associated with MJO water vapor and cloud anomalies and that propagation of the MJO is associated with advection of moist static energy. Both horizontal and vertical advection appear to play significant roles in the events studied here. Horizontal advection strongly moistens the atmosphere during the buildup to the active phase of the October event when the low-level winds switch from westerly to easterly. Horizontal advection strongly dries the atmosphere in the wake of the active phases of the November and December events as the westerlies associated with off-equatorial cyclonic gyres bring subtropical dry air into the convective region from the west and north. Vertical advection provides relative moistening ahead of the active phase and drying behind it, associated with an increase of the normalized gross moist stability.Atmospheric sciences, Remote sensing, Climate change, Applied mathematics, Madden-Julian oscillation, Atmospheric circulationahs129, sw2526Applied Physics and Applied MathematicsArticlesGlobal inventory and characterization of pyroclastic deposits on Mercury: New insights into pyroclastic activity from MESSENGER orbital datahttps://academiccommons.columbia.edu/catalog/ac:190195
Goudge, Timothy A.; Head, James W.; Kerber, Laura; Blewett, David T.; Denevi, Brett W.; Domingue, Deborah L.; Gillis-Davis, Jeffrey J.; Gwinner, Klaus; Helbert, Jörn; Holsclaw, Gregory M.; Izenberg, Noam R.; Kilma, Rachel L.; McClintock, William E.; Murchie, Scott L.; Neumann, Gregory A.; Smith, David E.; Strom, Robert G.; Xiao, Zhiyong; Zuber, Maria T.; Solomon, Sean C.http://dx.doi.org/10.7916/D8SQ8ZRWSun, 27 Sep 2015 13:31:22 +0000We present new observations of pyroclastic deposits on the surface of Mercury from data acquired during the orbital phase of the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) mission. The global analysis of pyroclastic deposits brings the total number of such identified features from 40 to 51. Some 90% of pyroclastic deposits are found within impact craters. The locations of most pyroclastic deposits appear to be unrelated to regional smooth plains deposits, except some deposits cluster around the margins of smooth plains, similar to the relation between many lunar pyroclastic deposits and lunar maria. A survey of the degradation state of the impact craters that host pyroclastic deposits suggests that pyroclastic activity occurred on Mercury over a prolonged interval. Measurements of surface reflectance by MESSENGER indicate that the pyroclastic deposits are spectrally distinct from their surrounding terrain, with higher reflectance values, redder (i.e., steeper) spectral slopes, and a downturn at wavelengths shorter than ~400 nm (i.e., in the near-ultraviolet region of the spectrum). Three possible causes for these distinctive characteristics include differences in transition metal content, physical properties (e.g., grain size), or degree of space weathering from average surface material on Mercury. The strength of the near-ultraviolet downturn varies among spectra of pyroclastic deposits and is correlated with reflectance at visible wavelengths. We suggest that this interdeposit variability in reflectance spectra is the result of either variable amounts of mixing of the pyroclastic deposits with underlying material or inherent differences in chemical and physical properties among pyroclastic deposits.Geomorphology, Remote sensing, Planetology, Volcanic ash, tuff, etc., Mercury (Planet)scs2186Lamont-Doherty Earth ObservatoryArticlesLand-surface controls on afternoon precipitation diagnosed from observational data: uncertainties and confounding factorshttps://academiccommons.columbia.edu/catalog/ac:178051
Guillod, B. P.; Orlowsky, B.; Miralles, D.; Teuling, A. J. ; Blanken, P. D.; Buchmann, N.; Ciais, P.; Ek, M.; Findell, K. L.; Gentine, Pierre; Lintner, Benjamin R.; Scott, R. L.; Van den Hurk, B.; Seneviratne, S. I.http://dx.doi.org/10.7916/D8FT8JM2Tue, 07 Oct 2014 09:48:32 +0000The feedback between soil moisture and precipitation has long been a topic of interest due to its potential for improving weather and seasonal forecasts. The generally proposed mechanism assumes a control of soil moisture on precipitation via the partitioning of the surface turbulent heat fluxes, as assessed via the evaporative fraction (EF), i.e., the ratio of latent heat to the sum of latent and sensible heat, in particular under convective conditions. Our study investigates the poorly understood link between EF and precipitation by relating the before-noon EF to the frequency of afternoon precipitation over the contiguous US, through statistical analyses of multiple EF and precipitation data sets. We analyze remote-sensing data products (Global Land Evaporation: the Amsterdam Methodology (GLEAM) for EF, and radar precipitation from the NEXt generation weather RADar system (NEXRAD)), FLUXNET station data, and the North American Regional Reanalysis (NARR). Data sets agree on a region of positive relationship between EF and precipitation occurrence in the southwestern US. However, a region of strong positive relationship over the eastern US in NARR cannot be confirmed with observation-derived estimates (GLEAM, NEXRAD and FLUXNET). The GLEAM–NEXRAD data set combination indicates a region of positive EF–precipitation relationship in the central US. These disagreements emphasize large uncertainties in the EF data. Further analyses highlight that much of these EF–precipitation relationships could be explained by precipitation persistence alone, and it is unclear whether EF has an additional role in triggering afternoon precipitation. This also highlights the difficulties in isolating a land impact on precipitation. Regional analyses point to contrasting mechanisms over different regions. Over the eastern US, our analyses suggest that the EF–precipitation relationship in NARR is either atmospherically controlled (from precipitation persistence and potential evaporation) or driven by vegetation interception rather than soil moisture. Although this aligns well with the high forest cover and the wet regime of that region, the role of interception evaporation is likely overestimated because of low nighttime evaporation in NARR. Over the central and southwestern US, the EF–precipitation relationship is additionally linked to soil moisture variations, owing to the soil-moisture-limited climate regime.Soil sciences, Atmospheric sciences, Remote sensingpg2328Earth and Environmental EngineeringWinter crop sensitivity to inter-annual climate variability in central Indiahttps://academiccommons.columbia.edu/catalog/ac:177543
Mondal, Pinki; Jain, Meha; Robertson, Andrew W.; Galford, Gillian L.; Small, Christopher; DeFries, Ruth S.http://dx.doi.org/10.7916/D81Z42XFWed, 17 Sep 2014 14:43:33 +0000India is predicted to be one of the most vulnerable agricultural regions to future climate changes. Here, we examined the sensitivity of winter cropping systems to inter-annual climate variability in a local market and subsistence-based agricultural system in central India, a data-rich validation site, in order to identify the climate parameters to which winter crops – mainly wheat and pulses in this region – might be sensitive in the future. We used satellite time-series data to quantify inter-annual variability in multiple climate parameters and in winter crop cover, agricultural census data to quantify irrigation, and field observations to identify locations for specific crop types. We developed three mixed-effect models (250 m to 1 km scale) to identify correlations between crop cover (wheat and pulses) and twenty-two climate and environmental parameters for 2001-2013. We find that winter daytime mean temperature (November–January) is the most significant factor affecting winter crops, irrespective of crop type, and is negatively associated with winter crop cover. With pronounced winter warming projected in the coming decades, effective adaptation by smallholder farmers in similar landscapes would require additional strategies, such as access to fine-scale temperature forecasts and heat-tolerant winter crop varieties.Agriculture, Remote sensing, South Asian studies, Climatic changespm2658, mj2415, awr2001, cs184, rd2402Ecology, Evolution, and Environmental Biology, International Research Institute for Climate and Society, Lamont-Doherty Earth ObservatoryArticlesFrequency-magnitude distribution of microearthquakes beneath the 9°50′N region of the East Pacific Rise, October 2003 through April 2004https://academiccommons.columbia.edu/catalog/ac:173407
Bohnenstiehl, Delwayne R.; Waldhauser, Felix; Tolstoy, Mariahttp://dx.doi.org/10.7916/D82B8W37Mon, 28 Apr 2014 12:55:31 +0000Relocated hypocentral data from a 7-month deployment (October 2003 to April 2004) of ocean bottom seismometers provide an opportunity to map microearthquake frequency-magnitude distributions (FMDs) along the 9°49–52′N region on the East Pacific Rise. These analyses, which incorporate more than 9000 earthquakes, represent the first investigation of the 3-D spatial and temporal patterns of FMDs along any mid-ocean ridge spreading center. The data are described well by a Gutenberg-Richter model, indicating a power law or fractal relationship between earthquake size and frequency. The scaling exponent, or b value, shows significant spatial variability, exceeding a value of 2.0 at the shallowest depths on axis and dropping below 1.0 away from the axial trough. This spatial pattern is consistent with an inverse relationship between b value and ambient stress conditions, with the lowest stress levels at shallow depths and relatively high stress levels (or low pore pressures) observed away from the axial zone. Intermediate b values are observed on-axis above the ridge system's melt lens; however, within this region there also exists significant spatial variability. This indicates that stress conditions and/or structural heterogeneity may vary at subkilometer scales within the hydrothermal circulation cell. Although the observational period is characterized by increasing seismicity rates, building toward an eruptive episode in January 2006, the first-order spatial pattern of b values is sustained, with no overall temporal trend. As a byproduct of this b value analysis, the detection capabilities of the array are assessed empirically.Remote sensing, Plate tectonicsdrb34, fw2005, mt290Lamont-Doherty Earth ObservatoryArticlesJanuary 2006 seafloor-spreading event at 9°50′N, East Pacific Rise: Ridge dike intrusion and transform fault interactions from regional hydroacoustic datahttps://academiccommons.columbia.edu/catalog/ac:173385
Dziak, Robert P. ; Bohnenstiehl, Delwayne R.; Matsumoto, Haruyoshi; Fowler, Matthew J. ; Haxel, Joseph H.; Tolstoy, Maria; Waldhauser, Felixhttp://dx.doi.org/10.7916/D89S1P46Mon, 28 Apr 2014 12:10:40 +0000An array of autonomous underwater hydrophones is used to investigate regional seismicity associated with the 22 January 2006 seafloor-spreading event on the northern East Pacific Rise near 9°50′N. Significant earthquake activity was observed beginning 3 weeks prior to the eruption, where a total of 255 earthquakes were detected within the vicinity of the 9°50′N area. This was followed by a series of 252 events on 22 January and a rapid decline to background seismicity levels during the subsequent 3 days. Because of their small magnitudes, accurate locations could be derived for only 20 of these events, 18 of which occurred during a 1-h period on 22 January. These earthquakes cluster near 9°45′N and 9°55′N, at the distal ends of the young lava flows identified posteruption, where the activity displays a distinct spatial-temporal pattern, alternating from the north to the south and then back to the north. This implies either rapid bilateral propagation along the rift or the near-simultaneous injection of melt vertically from the axial magma lens. Short-duration T wave risetimes are consistent with the eruption of lavas in the vicinity of 9°50′N on 22 January 2006. Eruptions on 12 and 15–16 January also may be inferred from the risetime data; however, the locations of these smaller-magnitude events cannot be determined accurately. Roughly 15 h after the last earthquakes were located adjacent to the eruption site, a sequence of 16 earthquakes began to the north-northeast at a distance of 25–40 km from the 9°50′N site. These events are located in vicinity of the Clipperton Transform and its western inside corner, an area from which the regional hydrophone network routinely detects seismicity. Coulomb stress modeling indicates that a dike intrusion spanning the known eruptive zone to the south (9°46′–9°56′N) would act to promote normal faulting or a combination of normal faulting and transform slip within this region, with stress changes on the order of 1–10 kPa.Remote sensing, Plate tectonicsdrb34, mt290, fw2005Lamont-Doherty Earth ObservatoryArticlesBack-arc extension in the Andaman Sea: Tectonic and magmatic processes imaged by high-precision teleseismic double-difference earthquake relocationhttps://academiccommons.columbia.edu/catalog/ac:173363
Diehl, Tobias; Waldhauser, Felix; Cochran, James R.; Kamesh Raju, K. A.; Seeber, Leonardo; Schaff, David P.; Engdahl, E. R.http://dx.doi.org/10.7916/D8ZK5DR9Mon, 28 Apr 2014 11:20:55 +0000The geometry, kinematics, and mode of back-arc extension along the Andaman Sea plate boundary are refined using a new set of significantly improved hypocenters, global centroid moment tensor (CMT) solutions, and high-resolution bathymetry. By applying cross-correlation and double-difference (DD) algorithms to regional and teleseismic waveforms and arrival times from International Seismological Centre and National Earthquake Information Center bulletins (1964–2009), we resolve the fine-scale structure and spatiotemporal behavior of active faults in the Andaman Sea. The new data reveal that back-arc extension is primarily accommodated at the Andaman Back-Arc Spreading Center (ABSC) at ~10°, which hosted three major earthquake swarms in 1984, 2006, and 2009. Short-term spreading rates estimated from extensional moment tensors account for less than 10% of the long-term 3.0–3.8 cm/yr spreading rate, indicating that spreading by intrusion and the formation of new crust make up for the difference. A spatiotemporal analysis of the swarms and Coulomb-stress modeling show that dike intrusions are the primary driver for brittle failure in the ABSC. While spreading direction is close to ridge normal, it is oblique to the adjacent transforms. The resulting component of E-W extension across the transforms is expressed by deep basins on either side of the rift and a change to extensional faulting along the West Andaman fault system after the Mw = 9.2 Sumatra-Andaman earthquake of 2004. A possible skew in slip vectors of earthquakes in the eastern part of the ABSC indicates an en-echelon arrangement of extensional structures, suggesting that the present segment geometry is not in equilibrium with current plate-motion demands, and thus the ridge experiences ongoing re-adjustment.Remote sensing, Plate tectonics, Geophysicsfw2005, jrc4, ls17, dps2004Lamont-Doherty Earth ObservatoryArticlesLove and Rayleigh phase-velocity maps, 5–40 s, of the western and central USA from USArray datahttps://academiccommons.columbia.edu/catalog/ac:169481
Ekström, Göranhttp://dx.doi.org/10.7916/D8T151NNFri, 24 Jan 2014 13:14:48 +0000Continuous data recorded on more than 1600 USArray seismic stations operating in the western and central US between 2006 and 2012 are used to map phase velocities of Love and Rayleigh waves at short periods (5–40 s) using a noise-correlation technique. Vertical and transverse records for all station pairs separated by less than 600 km are cross correlated in 4-h-long segments, and the resulting spectra are stacked for the time period of station operation. Dispersion curves are determined from the locations of zeros in the real component of the correlation spectra using a method based on that of Aki (1957). Phase-velocity maps expanded on a 0.25°-by-0.25° pixel grid are estimated by inversion of the phase-velocity measurements. Comparison with predicted phase-velocity maps based on the crustal model CRUST2.0 combined with the mantle model ND08 shows good agreement at the longer periods. Strong slow anomalies (greater than 25%) in the short-period maps are geographically correlated with basins and regions of thick sedimentary cover. The strength of these anomalies is not well predicted by existing crustal-velocity models.Geophysics, Plate tectonics, Remote sensingge21Lamont-Doherty Earth Observatory, Earth and Environmental SciencesArticlesDark Spots on Mercury: A Distinctive Low-Reflectance Material and Its Relation to Hollowshttps://academiccommons.columbia.edu/catalog/ac:171396
Xiao, Zhiyong; Strom, Robert G.; Blewett, David T.; Byrne, Paul K.; Solomon, Sean C.; Murchie, Scott L.; Sprague, Ann L.; Domingue, Deborah L.; Helbert, Jörnhttp://dx.doi.org/10.7916/D8Z31WMZWed, 22 Jan 2014 11:16:07 +0000Orbital images acquired by the Mercury, Surface, Space Environment, Geochemistry, and Ranging (MESSENGER) spacecraft reveal a distinctive low-reflectance material on the surface of Mercury. Such material occurs in small, isolated, and thin surficial units. We term these features “dark spots.” Dark spots have the lowest average reflectance yet documented on the planet. In every case observed at sufficiently high resolution, dark spots feature hollows at their centers. Not all hollows, however, are surrounded by a dark spot. Dark spots have been found on low-reflectance smooth plains, intercrater plains, heavily cratered terrain, and impact craters at almost all longitudes on Mercury, but they have not been documented on high-reflectance smooth plains material. Dark spots are one of the youngest endogenic features on Mercury, and some postdate craters with distinctive rays. Sulfides may be the phase responsible for the low albedo of dark spot material. We propose that dark spots form during the initial stages of hollow formation, perhaps in a manner similar to intense outgassing events that feature exit velocities in excess of 100 m/s. Such outgassing could contemporaneously produce a depression that constitutes an embryonic hollow. Under this scenario, dark spot material is subsequently removed or modified by regolith gardening or other surface processes on time scales shorter than the lifetime of the central hollow.Planetology, Remote sensing, Geophysicsscs2186Lamont-Doherty Earth ObservatoryArticlesAssimilation of remotely sensed soil moisture and vegetation with a crop simulation model for maize yield predictionhttps://academiccommons.columbia.edu/catalog/ac:165073
Ines, Amor Valeriano M.; Das, Narendra N.; Hansen, James W.; Njoku, Eni G.http://hdl.handle.net/10022/AC:P:21581Thu, 12 Sep 2013 16:22:17 +0000To improve the prediction of crop yields at an aggregate scale, we developed a data assimilation-crop modeling framework that incorporates remotely sensed soil moisture and leaf area index (LAI) into a crop model using sequential data assimilation. The core of the framework is an Ensemble Kalman Filter (EnKF) used to control crop model runs, assimilate remote sensing (RS) data and update model state variables. We modified the Decision Support System for Agro-technology Transfer – Cropping System Model (DSSAT-CSM)-Maize model (Jones et al., 2003) to be able to stop and start simulations at any given time in the growing season, such that the EnKF can update model state variables as RS data become available. The data assimilation-crop modeling framework was evaluated against 2003–2009 maize yields in Story County, Iowa, USA, assimilating AMSR-E soil moisture and MODIS-LAI data independently and simultaneously. Assimilating LAI or soil moisture independently slightly improved the correlation of observed and simulated yields (R = 0.51 and 0.50) compared to no data assimilation (open-loop; R = 0.47) but prediction errors improved with reductions in MBE and RMSE by 0.5 and 0.5 Mg ha− 1 respectively for LAI assimilation while these were reduced by 1.8 and 1.1 Mg ha− 1 for soil moisture assimilation. Yield correlation improved more when both soil moisture and LAI were assimilated (R = 0.65) suggesting a cause–effect interaction between soil moisture and LAI, prediction errors (MBE and RMSE) were also reduced by 1.7 and 1.8 Mg ha− 1 with respect to open-loop simulations. Results suggest that assimilation of LAI independently might be preferable when conditions are extremely wet while assimilation of soil moisture + LAI might be more suitable when conditions are more nominal. AMSR-E soil moisture tends to be more biased under the presence of high vegetation (i.e., when crops are fully developed) and that updating rootzone soil moisture by near-surface soil moisture assimilation under very wet conditions could increase the modeled percolation causing excessive nitrogen (N) leaching hence reducing crop yields even with water stress reduced at a minimum due to soil moisture assimilation. However, applying the data assimilation-crop modeling framework strategically by considering a-priori information on climate condition expected during the growing season may improve yield prediction performance substantially, in our case with higher correlation (R = 0.80) and more reductions in MBE and RMSE (2.5 and 3.3 Mg ha− 1) compared to when there is no data assimilation. Scaling AMSR-E soil moisture to the climatology of the model did not improve our data assimilation results because the model is also biased. Better soil moisture products e.g., from Soil Moisture Active Passive (SMAP) mission, may solve the soil moisture data issue in the near future.Remote sensing, Agriculture, Soil moisture, Crop yields--Data processing, Leaf area indexavi2101, jwh85International Research Institute for Climate and SocietyArticlesSpatial Variations in a Condensed Interval between Estuarine and Open-Marine Settings: Holocene Hudson River Estuary and Adjacent Continental Shelfhttps://academiccommons.columbia.edu/catalog/ac:164676
McHugh, Cecilia M.; Pekar, Stephen F.; Christie-Blick, Nicholas; Ryan, William B. F.; Carbotte, Suzanne M.; Bell, Robin E.http://hdl.handle.net/10022/AC:P:21469Wed, 28 Aug 2013 12:04:39 +0000An interval of stratigraphic condensation extending for 300 km from the fluvially dominated Hudson River estuary to the adjacent continental shelf reveals stratal relationships within an unconformity-related depositional sequence that are commonly difficult to resolve in seismic reflection profiles and outcrop. High-resolution side-scan sonar and bathymetry, more than 100 sediment cores ∼2 m long, and radioisotope (14C, 137Cs) age control show that much of the valley was filled by ca. 3 to 1 ka. The present rate of sediment accumulation averages 1 mm/yr, corresponding with a sea-level rise of ∼1.2 mm/yr relative to local bedrock. Condensation is manifested today by sedimentary bypass in most parts of the estuary and by the trapping of available sediment (1.2–5.6 × 105 t/yr [metric tons]) along narrow reaches and primarily in the vicinity of the estuarine turbidity maximum, a part of the estuary located upstream of the salinity intrusion ∼25 km from the mouth (3.0 × 105 t/yr). Shelf condensation is due to sediment starvation. The condensed interval merges updip with a nascent sequence boundary as the estuary reaches its final filling phase and downdip with the sequence boundary that developed at the Last Glacial Maximum. Delta progradation may take place as available shelf accommodation is filled, but such sediments are expected to be removed once sea level begins to fall. This sedimentation pattern, in which a condensed interval merges with different sequence boundaries, is consistent with the stratigraphic record of the Atlantic margin back to the Paleogene and may be typical of sediment-starved margins.Sedimentary geology, Remote sensing, Marine geologycmm4, sfp32, nc11, wbr1, smc29, reb4Lamont-Doherty Earth Observatory, Earth and Environmental SciencesArticlesSpectral Analysis of the Lower Eocene Wilkins Peak Member, Green River Formation, Wyoming: Support for Milankovitch Cyclicityhttps://academiccommons.columbia.edu/catalog/ac:164632
Machlus, Malka L.; Olsen, Paul E.; Christie-Blick, Nicholas; Hemming, Sidney R.http://hdl.handle.net/10022/AC:P:21455Tue, 27 Aug 2013 17:23:19 +0000This study is the first to employ spectral analysis to examine meter-scale sedimentary cyclicity in the Wilkins Peak Member of the lower Eocene Green River Formation of Wyoming. Generally regarded as the classic example for orbital forcing of lacustrine sediments at eccentricity and precession time scales, this long-standing interpretation was recently contested, with a much shorter duration (≤ 10 ky) inferred for the dominant cyclicity. Earlier work lacked adequate age control or spectral analysis or both. Our analysis is based upon an evaluation in the frequency domain of oil-yield values from four boreholes, accuracy estimation for suggested orbital interpretations, and comparison to independent geochronology. Cored intervals 266–364 m thick represent a span of 1.2–1.7 m.y., with temporal resolution of ∼ 3–5 ky (∼ 1 m) for oil-yield values. Variations in spectral power with depth within the original records are interpreted to reflect changes in the rate of sediment accumulation. These changes are corrected prior to testing the orbital forcing hypothesis by using two methods: 1) a minimal adjustment (three segments) accounting for the dominant changes of spectral frequency with depth; and 2) correlating the published definitions of precessional cycles in these records to a 21 ky cosine curve. Orbital age models resulting from the two tuning methods are compared to available chronology and the tuned records are tested for the expected spectral peaks from orbitally forced records. We conclude that the dominant cyclicity of the Wilkins Peak Member is orbitally forced. Orbital age models overlap 40Ar/39Ar ages and inferred periods include long and short eccentricity, weak obliquity and precession. Eccentricity is resolved in the analyzed records but the expected ∼ 95 and ∼ 125 ky periods are not resolved, controlling the range of possible tuning periods and the accuracy of orbital age models. Sub-Milankovitch variability exists and can be resolved to a minimum period of ∼ 3–5 ky by the analyzed records. However, it cannot be characterized fully with the available chronology or by the previously calculated mean cycle duration.Remote sensing, Sedimentary geology, Geomorphologymlm64, peo1, nc11, srh17Lamont-Doherty Earth Observatory, Earth and Environmental SciencesArticlesTechnical Comments: Sea Level Historyhttps://academiccommons.columbia.edu/catalog/ac:164572
Christie-Blick, Nicholas; Mountain, Gregory S.; Miller, Kenneth G.http://hdl.handle.net/10022/AC:P:21436Mon, 26 Aug 2013 14:42:03 +0000Bilal U. Haq and his co-workers have completed an important update of the chronology of coastal onlap and eustatic fluctuations in Mesowic and Cenowic time. Seismic stratigraphic results are augmented in the new charts by outcrop and well-log studies to document an impressive total of 119 sea level cycles since the beginning of the Triassic. In addition, the Cretaceous results have been published officially for the first time. However, apart from distinguishing between relative changes of coastal onlap and eustasy, the methodology and assumptions are much the same as those used to construct the first version of the "sea level curve" in 1977. In a recent evaluation of the seismic stratigraphic record of sea level change, we drew attention to two problems in particular. 1) All of the observed depositional cycles are assumed by Haq et al. to be eustatic. 2) The global onlap chart, which forms the basis for the smoothed eustatic curve, has little physical meaning.Marine geology, Remote sensing, Paleoclimate sciencenc11, gsm3Earth and Environmental Sciences, Lamont-Doherty Earth ObservatoryArticlesRock Deformation Studies in the Mineral Mountains and Sevier Desert of West-Central Utah: Implications for Upper Crustal Low-Angle Normal Faultinghttps://academiccommons.columbia.edu/catalog/ac:164560
Anders, Mark H.; Christie-Blick, Nicholas; Wills, Stewart; Krueger, Scot W.http://hdl.handle.net/10022/AC:P:21432Mon, 26 Aug 2013 13:24:06 +0000The Cave Canyon detachment, a low-angle normal fault that crops out in the Mineral Mountains, west-central Utah, has been interpreted as a hanging-wall splay of a much larger structure (the Sevier Desert detachment) that was influential in development of the idea that low-angle normal faults play a role in crustal extension. The Cave Canyon detachment provides expectations for the deformational features that might be expected along the hypothesized Sevier Desert detachment, which is not exposed in outcrop and is inferred to exist primarily on the basis of seismic reflection data.
The footwall of the Cave Canyon detachment is characterized by a 200-m-thick granite cataclasite, which exhibits a clear decrease in grain size and increase in microfracture density as the fault surface is approached. Undulatory extinction in quartz and feldspar and abundant quartz deformation lamellae at distances more than 200 m from the fault surface are interpreted as related to cooling of the Miocene granite rather than to normal faulting. Although mylonitic textures have previously been described in the granite, we found no evidence for mylonitization in the footwall rocks. The hanging wall of the detachment is characterized by 9 m of deformed, partially dolomitized limestone, with a 2-m-thick carbonate mylonite at the contact. Deformation features include dynamic recrystallization, grain-size reduction, development of twinning with a strong preferred orientation, some grain-size layering, and undulatory extinction close to the fault. Static recrystallization overprints fossils and ooids at distances greater than 9 m.
Drill cuttings and some core recovered at similar distances above and below the hypothesized Sevier Desert detachment show no evidence for localized deformation (ARCO Hole-in-the-Rock No. 1, ARCO Meadow Federal No. 1, and Argonaut Energy Federal No. 1 wells). Fossils and ooids are undeformed in Paleozoic carbonate rocks within 3 m below the contact, and sandstone and conglomerate with rounded clasts lacking more than background levels of microfracturing are found in samples within 3 m above the contact. These features contrast markedly with those of the Cave Canyon detachment, which was active at a considerably shallower and cooler level in the crust (∼5 km and less than 300 °C) than is implied for Paleozoic rocks beneath the Sevier Desert, once hanging-wall rocks are restored along the hypothesized detachment (9−14 km and 280−425 °C at the locations studied). The very different character of the two surfaces reinforces our earlier suggestion that beneath much of the Sevier Desert basin, the base of the Tertiary section is an unconformity rather than a low-angle normal fault.Plate tectonics, Remote sensing, Geologymha1, nc11Earth and Environmental SciencesArticlesExtensional Collapse along the Sevier Desert Reflection, Northern Sevier Desert Basin, Western United States: Comment and Replyhttps://academiccommons.columbia.edu/catalog/ac:164554
Anders, Mark H.; Christie-Blick, Nicholas; Wills, Stewart; Coogan, James C.; DeCelles, Peter G.http://hdl.handle.net/10022/AC:P:21431Mon, 26 Aug 2013 13:11:23 +0000Comment and reply on the Sevier Desert reflection debate.
Comment abstract: Coogan and DeCelles (1996) provided a welcome addition to the debate on the Sevier Desert reflection. The evidence and arguments presented on the nature of this subsurface feature merit particular scrutiny, as they bear directly on a first order issue in tectonics: the mechanical paradox of low-angle normal faults. Field geologists have argued that in some cases such faults must have moved at dips of 20° or less; tectonophysicists maintain that such interpretations are inconsistent with our present knowledge of rock mechanics, and seismologists have yet to record a single earthquake that can be related unequivocally to slip on a low-angle normal fault. If, as Coogan and DeCelles (1996) and others have argued, the seismically imaged Sevier Desert reflection of west-central Utah is a rooted detachment fault with as much as 39 km of top-to-the-west slip, the seismic-reflection geometry effectively requires normal-sense slip on a surface dipping 11°. We believe, however, that geometry can also support alternative interpretations.
Reply abstract: In their comparison of two seismic reflection profiles across the western margin of the Sevier Desert basin, Anders et al. fall victims to a classic pitfall of seismic interpretation—the misinterpretation of multiples as primary stratal reflections. Their error lies in ignoring the acquisition parameters of the two data sets and overlooking fundamental characteristics of long-path multiples. The industry profiles in their are published in Mitchell and McDonald (1987) for detailed inspection. We focus on two attributes of long-path multiples to document the error in Anders et al.’s analysis: the effects of fold on multiple identification and attenuation, and the periodicity of multiples.Geology, Plate tectonics, Remote sensingmha1, nc11Earth and Environmental SciencesArticlesMulti-scale standardized spectral mixture modelshttps://academiccommons.columbia.edu/catalog/ac:164323
Small, Christopher; Milesi, Cristinahttp://hdl.handle.net/10022/AC:P:21320Mon, 12 Aug 2013 12:57:58 +0000Linear spectral mixture models can be standardized by using endmembers that span the global mixing space. By combining the benefits of location-specific mixture models with standardized spectral indices, standardized mixture models offer consistency, simplicity, inclusivity and applicability. We construct a globally representative mixing space using a spectrally diverse collection of 100 Landsat ETM+ (Thematic Mapper and Enhanced Thematic Mapper +) subscenes. Global composites of 100,000,000 Landsat spectra, constructed from both exoatmospheric reflectance and atmospherically corrected surface reflectance, represent the spectral diversity of a wide range of terrestrial environments. Principal Component (PC) Analysis of the global composite shows that 99% of the spectral variance can be represented in a 3-dimensional mixing space of the low order PCs. Within this 3D space 98% of spectra are contained within a tetrahedral hull bounded by a continuous plane of substrates, and well-defined apexes corresponding to vegetation and dark endmembers. Suites of individual substrate, vegetation and dark endmember spectra are used to derive mean endmembers and to quantify the effects of endmember variability on fractions estimated from a standardized Substrate, Vegetation, and Dark (SVD) linear mixture model. Maximum endmember variability introduces less than 0.05 difference in S, V, and D fractions for most SVD models constructed from individual pixel endmember spectra giving less than 0.05 model misfit for more than 97% of pixels in the global composite. The mean SVD endmembers define a standard global mixture model for Landsat spectra. These SVD endmembers can be used to model mixed reflectance spectra from other sensors with similar spectral responses to Landsat ETM+. Comparisons of endmember fractions estimated from coincident acquisitions of Landsat TM and ETM + and WorldView-2 imagery show strong linear scaling for vegetation and dark fractions. Substrate fractions do not scale as linearly for the urban validation sites because the Landsat substrate endmember does not accurately represent the impervious surfaces imaged by WorldView-2. Comparisons of Landsat and WorldView-2 unmixed with the same Visible-Near Infrared (VNIR) endmembers derived from the global Landsat endmembers are also strongly correlated but with reduced bias. This linear scaling suggests that the Landsat global endmembers may provide a basis for standardized mixture models for WorldView-2 and other broadband sensors with spectral response similar to Landsat TM and ETM+. Comparisons of vegetation fractions with vegetation indices for the global composite show strong linear correspondence for Tasseled Cap Greenness and Enhanced Vegetation Index, with some degree of saturation at high fractions for the Soil Adjusted Vegetation Index and a wide range of responses for the Normalized Difference Vegetation Index.Geology, Remote sensingcs184Lamont-Doherty Earth ObservatoryArticlesShort-Pulse Pump-And-Probe Technique for Airborne Laser Assessment of Photosystem II Photochemical Characteristicshttps://academiccommons.columbia.edu/catalog/ac:163803
Chekalyuk, Alexander M.; Hoge, Frank E.; Wright, Charles W.; Swift, Robert N.http://hdl.handle.net/10022/AC:P:21218Sat, 03 Aug 2013 19:15:26 +0000The development of a technique for laser measurement of fPhotosystem II (PS II) photochemical characteristics of phytoplankton and terrestrial vegetation from an airborne platform is described. Results of theoretical analysis and experimental study of pump-and-probe measurement of the PS II functional absorption cross-section and photochemical quantum yield are presented. The use of 10 ns probe pulses of PS II sub-saturating intensity provides a significant, up to 150-fold, increase in the fluorescence signal compared to conventional 'weak-probe' protocol. Little effect on the fluorescence yield from the probe-induced closure of PS II reaction centers is expected over the short pulse duration, and thus a relatively intense probe pulse can be used. On the other hand, a correction must be made for the probe-induced carotenoid triplet quenching and singlet-singlet annihilation. A Stern-Volmer model developed for this correction assumes a linear dependence of the quenching rate on the laser pulse fluence, which was experimentally validated. The PS II saturating pump pulse fluence (532 nm excitation) was found to be 10 and 40 mumol quanta m(-2) for phytoplankton samples and leaves of higher plants, respectively. Thirty mus was determined as the optimal delay in the pump-probe pair. Our results indicate that the short-pulse pump-and-probe measurement of PS II photochemical characteristics can be implemented from an airborne platform using existing laser and LIDAR technologies.Microbiology, Plant biology, Remote sensingac2709Lamont-Doherty Earth ObservatoryArticlesAn unmixing algorithm for remotely sensed soil moisturehttps://academiccommons.columbia.edu/catalog/ac:161816
Ines, Amor Valeriano M.; Mohanty, Binayak P.; Shin, Yongchulhttp://hdl.handle.net/10022/AC:P:20558Tue, 04 Jun 2013 13:12:05 +0000We present an unmixing method, based on genetic algorithm-soil-vegetation-atmosphere-transfer modeling to extract subgrid information of soil and vegetation from remotely sensed soil moisture (downscaled; e.g., soil hydraulic properties, area fractions of soil-vegetation combinations, and unmixed soil moisture time series) that most land surface models use. The unmixing method was evaluated using numerical experiments comprising mixed pixels with simple and complex soil-vegetation combinations, in idealized case studies (with or without uncertainty) and under actual field conditions (Walnut Creek (WC11) field, Soil Moisture Experiment 2005, Iowa). Additional validation experiments were conducted at an airborne-remote sensing footprint (Little Washita (LW21) site, Southern Great Plains 1997 hydrology campaign, Oklahoma) using Electronically Scanning Thin Array Radiometer (ESTAR). Results of the idealized experiments suggest that the unmixing method can extract optimal or near-optimal solutions to the inverse problem under different hydrologic and climatic conditions. Errors in soil moisture data and initial and boundary conditions can compound uncertainty in the solution. The solutions generated under actual field conditions (WC11 field) were able to match soil moisture observations. Analysis showed that typical soil moisture retention curves of cataloged dominant soils in WC11 field did not match well with the measurements, but those derived from actual field-scale soil moisture inversion matched better. The unmixing method performed well in replicating soil hydraulic behavior at the ESTAR footprint. Unlike in WC11 field, the typical soil moisture retention curves of cataloged soils in LW21 field matched better with the measurements. We envisaged that the unmixing method can provide quick and easy way of extracting subgrid soil moisture variability and soil-vegetation information in a pixel.Remote sensing, Water resources managementavi2101International Research Institute for Climate and SocietyArticlesMapping cropping intensity of smallholder farms: A comparison of methods using multiple sensorshttps://academiccommons.columbia.edu/catalog/ac:161216
Jain, Meha; Mondal, Pinki; DeFries, Ruth S.; Small, Christopher; Galford, Gillian L.http://hdl.handle.net/10022/AC:P:20348Fri, 17 May 2013 10:05:38 +0000The food security of smallholder farmers is vulnerable to climate change and climate variability. Cropping intensity, the number of crops planted annually, can be used as a measure of food security for smallholder farmers given that it can greatly affect net production. Current techniques for quantifying cropping intensity may not accurately map smallholder farms where the size of one field is typically smaller than the spatial resolution of readily available satellite data. We evaluated four methods that use multi-scalar datasets and are commonly used in the literature to assess cropping intensity of smallholder farms: 1) the Landsat threshold method, which identifies if a Landsat pixel is cropped or uncropped during each growing season, 2) the MODIS peak method, which determines if there is a phenological peak in the MODIS Enhanced Vegetation Index time series during each growing season, 3) the MODIS temporal mixture analysis, which quantifies the sub-pixel heterogeneity of cropping intensity using phenological MODIS data, and 4) the MODIS hierarchical training method, which quantifies the sub-pixel heterogeneity of cropping intensity using hierarchical training techniques. Each method was assessed using four criteria: 1) data availability, 2) accuracy across different spatial scales (at aggregate scales 250 × 250 m, 1 × 1 km, 5 × 5 km, and 10 × 10 km), 3) ease of implementation, and 4) ability to use the method over large spatial and temporal scales. We applied our methods to two regions in India (Gujarat and southeastern Madhya Pradesh) that represented diversity in crop type, soils, climatology, irrigation access, cropping intensity, and field size. We found that the Landsat threshold method is the most accurate (R2 greater than or equal to 0.71 and RMSE less than or equal to 0.14), particularly at smaller scales of analysis. Yet given the limited availability of Landsat data, we find that the MODIS hierarchical training method meets multiple criteria for mapping cropping intensity over large spatial and temporal scales. Furthermore, the adjusted R2 between predicted and validation data generally increased and the RMSE decreased with spatial aggregation greater than or equal to 5 × 5 km (R2 up to 0.97 and RMSE as low as 0.00). Our model accuracy varied based on the region and season of analysis and was lowest during the summer season in Gujarat when there was high sub-pixel heterogeneity due to sparsely cropped agricultural land-cover. While our results specifically apply to our study regions in India, they most likely also apply to smallholder agriculture in other locations across the globe where the same types of satellite data are readily available.Agriculture, Remote sensing, South Asian studiesmj2415, pm2658, rd2402, cs184, gg2405Ecology, Evolution, and Environmental Biology, Lamont-Doherty Earth Observatory, Earth InstituteArticlesRecent trends in Inner Asian forest dynamics to temperature and precipitation indicate high sensitivity to climate changehttps://academiccommons.columbia.edu/catalog/ac:157559
Poulter, Benjamin; Pederson, Neil; Liu, Hongyan; Zhu, Zaichun; D'Arrigo, Rosanne Dorothy; Ciais, Philippe; Davi, Nicole K.; Frank, David; Leland, Caroline Wogan; Myeni, Ranga; Piao, Shilong; Wang, Taohttp://hdl.handle.net/10022/AC:P:19348Thu, 14 Mar 2013 11:33:35 +0000Semi-arid ecosystems play an important role in regulating global climate with the fate of these ecosystems in the Anthropocene depending upon interactions among temperature, precipitation, and CO₂. However, in cool-arid environments, precipitation is not the only limitation to forest productivity. Interactions between changes in precipitation and air temperature may enhance soil moisture stress while simultaneously extending growing season length, with unclear consequences for net carbon uptake. This study evaluates recent trends in productivity and phenology of Inner Asian forests (in Mongolia and Northern China) using satellite remote sensing, dendrochronology, and dynamic global vegetation model (DGVM) simulations to quantify the sensitivity of forest dynamics to decadal climate variability and trends. Trends in photosynthetically active radiation fraction (FPAR) between 1982 and 2010 show a greening of about 7% of the region in spring (March, April, May), and 3% of the area ‘browning’ during summertime (June, July, August). These satellite observations of FPAR are corroborated by trends in NPP simulated by the LPJ DGVM. Spring greening trends in FPAR are mainly explained by long-term trends in precipitation whereas summer browning trends are correlated with decreasing precipitation. Tree ring data from 25 sites confirm annual growth increments are mainly limited by summer precipitation (June, July, August) in Mongolia, and spring precipitation in northern China (March, April, May), with relatively weak prior-year lag effects. An ensemble of climate projections from the IPCC CMIP3 models indicates that warming temperatures (spring, summer) are expected to be associated with higher summer precipitation, which combined with CO₂ causes large increases in NPP and possibly even greater forest cover in the Mongolian steppe. In the absence of a strong direct CO₂ fertilization effect on plant growth (e.g., due to nutrient limitation), water stress or decreased carbon gain from higher autotrophic respiration results in decreased productivity and loss of forest cover. The fate of these semi-arid ecosystems thus appears to hinge upon the magnitude and subtleties of CO₂ fertilization effects, for which experimental observations in arid systems are needed to test and refine vegetation models.Ecology, Biogeochemistry, Remote sensing, Climate changenp150, rd5, nkd5, cwl2130Lamont-Doherty Earth Observatory, Earth and Environmental SciencesArticlesNight on Earth: Mapping decadal changes of anthropogenic night light in Asiahttps://academiccommons.columbia.edu/catalog/ac:151673
Small, Christopher; Elvidge, Christopher D.http://hdl.handle.net/10022/AC:P:14393Wed, 15 Aug 2012 13:29:11 +0000The defense meteorological satellite program (DMSP) operational linescan system (OLS) sensors have imaged emitted light from Earth's surface since the 1970s. Temporal overlap in the missions of 5 OLS sensors allows for intercalibration of the annual composites over the past 19 years (Elvidge et al., 2009). The resulting image time series captures a spatiotemporal signature of the growth and evolution of lighted human settlements and development. We use empirical orthogonal function (EOF) analysis and the temporal feature space to characterize and quantify patterns of temporal change in stable night light brightness and spatial extent since 1992. Temporal EOF analysis provides a statistical basis for representing spatially abundant temporal patterns in the image time series as uncorrelated vectors of brightness as a function of time from 1992 to 2009. The variance partition of the eigenvalue spectrum combined with temporal structure of the EOFs and spatial structure of the PCs provides a basis for distinguishing between deterministic multi-year trends and stochastic year-to-year variance. The low order EOFs and principal components (PC) space together discriminate both earlier (1990s) and later (2000s) increases and decreases in brightness. Inverse transformation of these low order dimensions reduces stochastic variance sufficiently so that tri-temporal composites depict potentially deterministic decadal trends. The most pronounced changes occur in Asia. At critical brightness threshold we find an 18% increase in the number of spatially distinct lights and an 80% increase in lighted area in southern and eastern Asia between 1992 and 2009. During this time both China and India experienced a ∼20% increase in number of lights and a ∼270% increase in lighted area – although the timing of the increase is later in China than in India. Throughout Asia a variety of different patterns of brightness increase are apparent in tri-temporal brightness composites – as well as some conspicuous areas of apparently decreasing background luminance and, in many places, intermittent light suggesting development of infrastructure rather than persistently lighted development. Vicarious validation using higher resolution Landsat imagery verifies multiple phases of urban growth in several cities as well as the consistent presence of low DN (<∼15) background luminance for many agricultural areas. Lights also allow us to quantify changes in the size distribution and connectedness of different intensities of development. Over a wide range of brightnesses, the size distributions of spatially contiguous lighted area are consistent with power laws with exponents near −1 as predicted by Zipf's Law for cities. However, the larger lighted segments are much larger than individual cities; they correspond to vast spatial networks of contiguous development (Small et al., 2011).Remote sensingcs184Lamont-Doherty Earth Observatory, Earth and Environmental SciencesArticlesSpatiotemporal dimensionality and Time-Space characterization of multitemporal imageryhttps://academiccommons.columbia.edu/catalog/ac:151670
Small, Christopherhttp://hdl.handle.net/10022/AC:P:14392Wed, 15 Aug 2012 13:13:21 +0000Spatiotemporal dimensionality refers to the continuum of spatial and temporal patterns in an image time series. Time-Space characterization refers to a way of representing this continuum of patterns as combinations of spatial and temporal constituents — with a minimum of assumptions about the forms of the patterns. Patterns can be related to processes through modeling. By combining characterization and modeling, two complementary analytical tools can be used together so that each resolves a key limitation of the other. This study describes a straightforward extension of Principal Component Analysis and Spectral Mixture Analysis to multitemporal imagery and illustrates how characterization of the dimensionality and eigenstructure of the data can inform modeling of the processes represented in the data. The relationships among spatiotemporal processes can be represented as combinations of temporal endmembers in a temporal feature space where the dimensions represent different components of the temporal patterns present in the data. The topology of the feature space and the processes being modeled together inform the selection of temporal endmembers and the structure of the model chosen to represent the processes. The dimensionality revealed by the characterization can also provide a partial solution to the problem of endmember variability. The characterization and modeling process is illustrated with the vegetation phenology of the Ganges–Brahmaputra delta using a MODIS vegetation index time series. Additional applications and limitations of Time-Space characterization and mixture modeling are further illustrated by comparing the eigenstructures and temporal feature spaces of Landsat vegetation fraction and DMSP-OLS night light time series.Remote sensingcs184Lamont-Doherty Earth Observatory, Earth and Environmental SciencesArticlesApplication of GIS and crop growth models in estimating water productivityhttps://academiccommons.columbia.edu/catalog/ac:150562
Ines, Amor Valeriano M.; Das Gupta, Ashim; Loof, Rainerhttp://hdl.handle.net/10022/AC:P:14214Tue, 24 Jul 2012 10:16:14 +0000Tighter competition in water use is projected in the future. As water demand increases, water related problems could happen along the way. Accordingly, issues on water availability and use could be crucial to study to search for ways and means on how to cope up with the present trend. Sound water management practices could play a key role to the solution of problems relating to water availability and use. Water use in agriculture is considered the highest among other water users because of the water intensive processes involved in it. Aside from the crop water requirements, water loss, which are not beneficial to crop processes can add a huge volume to the total water usage in agriculture. Base from this argument, there could be greater possibility to save water from agriculture, which can be used for other purposes thereafter. To explore this option, analysis at the crop level could be beneficial. However, the issue of scaling should be also considered because the knowledge on the field scale could not be generally true in the basin scale. The objective of the study was to apply crop growth simulation models coupled with geographic information system (GIS) to analyze water productivity, which is an indicator of water use efficiency, at the basin scale. The methodology was applied to Laoag River Basin in Ilocos Norte, Philippines to study water productivity in spatial and temporal dimensions. Three crops were considered in the analysis: rice, maize and peanut. Simulations were done for both existing and potential agricultural areas. The potential productions of the selected crops from October 1996–September 1997 were used as bases in determining water productivity for the three cropping seasons (CS) being considered in the study. Water-limited productions were simulated for each of the crops, for each of the CS in the basin. Moreover, a marginal productivity analysis was done to determine the potential of water for crop production in the basin. Subsequently, the significance of irrigation was emphasized in the analysis when availability of water, and the combination of water and nitrogen (N) are limiting, respectively. The results showed that the spatio-temporal analysis of water productivity could provide substantial information for water saving opportunities and, hence, strategies in irrigated agriculture.Water resources management, Remote sensingavi2101International Research Institute for Climate and SocietyArticlesCombining remote sensing-simulation modeling and genetic algorithm optimization to explore water management options in irrigated agriculturehttps://academiccommons.columbia.edu/catalog/ac:150529
Ines, Amor Valeriano M.; Honda, Kiyoshi; Das Gupta, Ashim; Droogers, Peter; Clemente, Roberto S.http://hdl.handle.net/10022/AC:P:14207Mon, 23 Jul 2012 14:08:33 +0000We present an innovative approach to explore water management options in irrigated agriculture considering the constraints of water availability and the heterogeneity of irrigation system properties. The method is two-folds: (i) system characterization using a stochastic data assimilation procedure where the irrigation system properties and operational management practices are estimated using remote sensing (RS) data; and (ii) water management optimization where we explored water management options under various levels of water availability. We set up a soil–water–atmosphere–plant model (SWAP) in a deterministic–stochastic mode for regional modeling. The distributed data, e.g. sowing dates, irrigation practices, soil properties, depth to groundwater and water quality, required as inputs for the regional modeling were estimated by minimizing the residuals between the distributions of field-scale evapotranspiration (ET) simulated by the regional application of SWAP, and by surface energy balance algorithm for land (SEBAL) using two Landsat7 ETM+ images. The derived distributed data were used as inputs in exploring water management options. Genetic algorithm was used in data assimilation and water management optimizations. The case study was conducted in Bata minor (lateral canal), Kaithal, Haryana, India during 2000–2001 rabi (dry) season. Our results showed that under limited water condition, regional wheat yield could improve further if water and crop management practices are considered simultaneously and not independently. Adjusting sowing dates and their distribution in the irrigated area could improve the regional yield, which also complements the practice of deficit irrigation when water availability is largely a constraint. This result was also found in agreement with the scenario that water is non-limited with the exception that the farmers have more degrees of freedom in their agricultural activities. An improvement of the regional yield to 8.5% is expected under the current scenario.Water resources management, Remote sensing, Irrigation farmingavi2101International Research Institute for Climate and SocietyArticlesOn quantifying agricultural and water management practices from low spatial resolution RS data using genetic algorithms: A numerical study for mixed-pixel environmenthttps://academiccommons.columbia.edu/catalog/ac:150526
Ines, Amor Valeriano M.; Honda, Kiyoshihttp://hdl.handle.net/10022/AC:P:14206Mon, 23 Jul 2012 13:57:51 +0000In this paper, we present a genetic algorithm-based methodology to quantify agricultural and water management practices from remote sensing (RS) data in a mixed-pixel environment. First, we formulated a linear mixture model for low spatial resolution RS data where we considered three agricultural land uses as dominant inside the pixel—rainfed, irrigated with two, and three croppings a year; the mixing parameters we considered were the sowing dates, area fractions of agricultural land uses in the pixel, and their corresponding water management practices. Then, we carried out numerical experiments to evaluate the feasibility of the proposed approach. In the process, the mixing parameters were parameterized by data assimilation using evapotranspiration and leaf area index as conditioning criteria. The soil–water–atmosphere–plant system model SWAP was used to simulate the dynamics of these two biophysical variables in the pixel. The results of our numerical experiments showed that it is possible to derive some sub-pixel information from low spatial resolution data e.g. the existing agricultural and water management practices in a region, which are relevant for regional agricultural monitoring programs.Water resources management, Remote sensingavi2101International Research Institute for Climate and SocietyArticlesInverse Modeling to Quantify Irrigation System Characteristics and Operational Managementhttps://academiccommons.columbia.edu/catalog/ac:150501
Ines, Amor Valeriano M.; Droogers, Peterhttp://hdl.handle.net/10022/AC:P:14203Mon, 23 Jul 2012 13:09:27 +0000Remotely sensed (RS) data is a major source to obtain spatial data required for hydrological models. The challenge for the future is to obtain besides the more direct observable data (landcover, leaf area index, digital elevation model and evapotranspiration), non-visible data such as soil characteristics, groundwater depth and irrigation practices.In this study we have explore the option of using inverse modeling to obtain these non-RS-visible data. For a command area in Haryana, India, we applied for the 2000–2001 rabi season a RS-GIS-combined inverse modeling approach to derive non-RS-visible data required in the regional application of hydrological models. A Genetic Algorithm loaded stochastic physically based soil-water-atmosphere-plant model (SWAP) was developed for the inverse problem and used in the study. The results showed good agreement with the inventoried data such as soil hydraulic properties, sowing dates, ground water depths, irrigation practices and water quality. The derived data could be used to predict the state of the system at anytime in the cropping season, which can be used to evaluate operational management strategies.Hydrologic sciences, Remote sensingavi2101International Research Institute for Climate and SocietyArticlesGravity gradiometry resurfaceshttps://academiccommons.columbia.edu/catalog/ac:144581
Bell, Robin E.; Anderson, Roger N.; Pratson, Lincoln F.http://hdl.handle.net/10022/AC:P:12548Mon, 13 Feb 2012 15:51:00 +0000Twelve years ago, reading a passage from the submarine novel The Hunt for Red October by Tom Clancy was as dose as any exploration geophysicist got to gravity gradiometry. This early technique in Gulf Coast exploration, which faded from use with the development of modern gravity instrumentation in the 1930s, had been relegated to brief historical sections of introductory texts. In the 1970s, driven by both navigation and missile launching requirements, the U.S. Navy spent hundreds of millions of dollars developing a system to measure gravity gradients; this system was somewhat more complex than the fictional one Clancy installed on the Red October. The end of the Cold War triggered the introduction of classified military technology to exploration geophysics and other fields. Three years ago the U.S. Navy began to explore civilian applications for submarine gravity gradient technology. This article describes gravity gradients, the developing uses of gravity gradiometry in exploration, and future possibilities for the technique.Geology, Geophysics, Remote sensingreb4, rna1Lamont-Doherty Earth Observatory, Center for Computational Learning SystemsArticlesEvaluation of the BGM-3 sea gravity meter system onboard R/V Conradhttps://academiccommons.columbia.edu/catalog/ac:144575
Bell, Robin E.; Watts, Anthony B.http://hdl.handle.net/10022/AC:P:12546Mon, 13 Feb 2012 15:29:48 +0000The first Bell Aerospace BGM-3 Marine Gravity Meter System available for academic use was installed on R/V Robert D. Conrad in February, 1984. The BGM-3 system consists of a forced feedback accelerometer mounted on a gyrostabilized platform. Its sensor (requiring no cross-coupling correction) is a significant improvement over existing beam and spring-type sea gravimeters such as the GSS-2. A gravity survey over the Wallops Island test range together with the results of subsequent cruises allow evaluation of the precision, accuracy, and capabilities of the new system. Over the test range, the BGM-3 data were compared directly to data obtained by a GSS-2 meter onboard R/V Conrad. The rms discrepancy between free-air gravity anomaly values at intersecting ship tracks of R/V Conrad was ±0.38 mGal for BGM-3 compared to ±1.60 mGal for the GSS-2. Moreover, BGM-3's platform recovered from abrupt changes in ship's heading more rapidly than did the platform of GSS-2. The principal factor limiting the accuracy of sea gravity data is navigation. Over the test range, where navigation was by Loran C and transit satellite, a two-step filtering of the ship's velocity and position was required to obtain an optimal Eötvös correction. A spectral analysis of 1 minute values of the Eötvös correction and the reduced free-air gravity anomaly determined the filter characteristics. To minimize the coherence between the Eötvös and free-air anomaly, it was necessary to prefilter the ship's position and velocity. Using this procedure, reduced free-air gravity anomalies with wavelengths as small as a few kilometers can be resolved.Geology, Geophysics, Remote sensingreb4Lamont-Doherty Earth ObservatoryArticlesAirborne gravimetry from a small twin engine aircraft over the Long Island Soundhttps://academiccommons.columbia.edu/catalog/ac:144572
Bell, Robin E.; Coakley, Bernard J.; Stemp, Robert W.http://hdl.handle.net/10022/AC:P:12545Mon, 13 Feb 2012 15:24:46 +0000In January 1990, a test of the feasibility of airborne gravimetry from a small geophysical survey aircraft, a Cessna 404, was conducted over the Long Island Sound using a Bell Aerospace BGM-3 sea gravity meter. Gravity has been measured from large aircraft and specially modified de Havilland Twin Otters but never from small, standard survey aircraft. The gravity field of the Long Island Sound is dominated by an asymmetric positive 30 mGal anomaly which is well constrained by both marine and land gravity measurements. Using a Trimble 4000 GPS receiver to record the aircraft's horizontal position and radar altimeter elevations to recover the vertical accelerations, gravity anomalies along a total of 65 km were successfully measured. The root mean square (rms) difference between the airborne results and marine measurements within 2 km of the flight path was 2.6 mGal for 15 measured values. The anomalies recovered from airborne gravimetry can also be compared with the gridded regional free air gravity field calculated using all available marine and land gravity measurements. The rms difference between 458 airborne gravity measurements and the regional gravity field is 2.7 mGal. This preliminary experiment demonstrates that gravity anomalies, with wavelengths as short as 5 km, can be measured from small aircraft with accuracies of 2.7 mGal or better. The gravity measurements could be improved by higher quality vertical and horizontal positioning and tuning the gravimeter's stabilized platform for aircraft use.Geology, Remote sensingreb4Lamont-Doherty Earth ObservatoryArticlesSoil hydraulic parameters estimated from satellite information through data assimilationhttps://academiccommons.columbia.edu/catalog/ac:144148
Charoenhirunyingyos, Sujittra; Honda, Kiyoshi; Kamthonkiat, Daroonwan; Ines, Amor Valeriano M.http://hdl.handle.net/10022/AC:P:12473Tue, 07 Feb 2012 10:40:16 +0000Leaf area index (LAI) and actual evapotranspiration (ETa) from satellite observations were used to estimate simultaneously the soil hydraulic parameters of four soil layers down to 60 cm depth using the combined soil water atmosphere plant and genetic algorithm (SWAP-GA) model. This inverse model assimilates the remotely sensed LAI and/or ETa by searching for the most appropriate sets of soil hydraulic parameters that could minimize the difference between the observed and simulated LAI (LAIsim) or simulated ETa (ETasim). The simulated soil moisture estimates derived from soil hydraulic parameters were validated using values obtained from soil moisture sensors installed in the field. Results showed that the soil hydraulic parameters derived from LAI alone yielded good estimations of soil moisture at 3 cm depth; LAI and ETa in combination at 12 cm depth, and ETa alone at 28 cm depth. There appeared to be no match with measurement at 60 cm depth. Additional information would therefore be needed to better estimate soil hydraulic parameters at greater depths. Despite this inability of satellite data alone to provide reliable estimates of soil moisture at the lowest depth, derivation of soil hydraulic parameters using remote sensing methods remains a promising area for research with significant application potential. This is especially the case in areas of water management for agriculture and in forecasting of floods or drought on the regional scale.Hydrologic sciences, Remote sensing, Leaf area index, Evapotranspiration, Soil moisture--Remote sensingavi2101International Research Institute for Climate and SocietyArticlesSoil moisture estimation from inverse modeling using multiple criteria functionshttps://academiccommons.columbia.edu/catalog/ac:144142
Charoenhirunyingyos, Sujittra; Honda, Kiyoshi; Kamthonkiat, Daroonwan; Ines, Amor Valeriano M.http://hdl.handle.net/10022/AC:P:12471Tue, 07 Feb 2012 10:14:14 +0000Soil hydraulic parameters are essential inputs to agricultural and hydrologic models for simulating soil moisture. These parameters however are difficult to obtain especially when the application is aimed at the regional scale. Laboratory and field methods have been used for quantifying soil hydraulic parameters but they are proved to be laborious and expensive. An emerging alternative of estimating soil hydraulic parameters is soil moisture model inversion using remote sensing (RS) data. Although soil hydraulic parameters could not be derived directly from remote sensing, they could be quantified by the inverse modeling of RS data. In this study, we conducted a multi-criteria inverse modeling approach to estimate the rootzone soil hydraulic parameters in a rainfed rice field at depths 3, 12, 28 and 60 cm, respectively. The conditioning data used in the inverse modeling are leaf area index (LAI) and actual evapotranspiration (ETa) from satellite imageries, and soil moisture (SM) data from in situ measurements. The performances of all the model inversion experiments were evaluated against observed soil moisture in the field, and measured LAI during the growing season. The results showed that using remotely sensed LAI and ETa in the inverse modeling provided a good matching between observed and simulated soil moisture down to 28 cm depth from the soil surface. With the addition of soil moisture information from the site, the model inversion significantly improved the soil moisture simulation up to a depth of 60 cm.Hydrologic sciences, Remote sensing, Soil moisture--Remote sensing, Evapotranspiration, Leaf area indexavi2101International Research Institute for Climate and SocietyArticlesAdvanced laser fluorometry of natural aquatic environmentshttps://academiccommons.columbia.edu/catalog/ac:143904
Chekalyuk, Alexander M.; Hafez, Mark A.http://hdl.handle.net/10022/AC:P:12411Tue, 31 Jan 2012 11:54:57 +0000The Advanced Laser Fluorometer (ALF) provides spectral deconvolution (SDC) analysis of the laser-stimulated emission (LSE) excited at 405 or 532 nm for assessment of chlorophyll a, phycoerythrin, and chromophoric dissolved organic matter. Three spectral types of phycoerythrin are discriminated for characterization of cyanobacteria and cryptophytes in mixed phototrophic populations. The SDC analysis is integrated with measurements of variable fluorescence, Fv/Fm, corrected for the SDC-retrieved background fluorescence, BNC, for improved photophysiological assessments of phytoplankton. The ALF deployments in the Atlantic and Pacific Oceans, and Chesapeake, Delaware, and Monterey Bays revealed significant spectral complexity of LSE. Considerable variability in chlorophyll a fluorescence peak, 673-685 nm, was detected. High correlation (R2 = 0.93) was observed in diverse water types between chlorophyll a concentration and fluorescence normalized to water Raman scattering. Three unidentified red bands, peaking at 625, 644, and 662 nm, were detected in the LSE excited at 405 nm. Significant variability in the BNC/chlorophyll a ratio was observed in diverse waters. Examples of the ALF spectral correction of Fv/Fm, underway shipboard measurements of horizontal variability, and vertical distributions compiled from the discrete samples analyses are presented. The field deployments have demonstrated the utility of the ALF technique as an integrated tool for research and observations.Optics, Remote sensing, Physical oceanographyac2709, mh3170Lamont-Doherty Earth ObservatoryArticlesPhoto-physiological variability in phytoplankton chlorophyll fluorescence and assessment of chlorophyll concentrationhttps://academiccommons.columbia.edu/catalog/ac:143901
Chekalyuk, Alexander M.; Hafez, Mark A.http://hdl.handle.net/10022/AC:P:12409Tue, 31 Jan 2012 11:54:11 +0000Photo-physiological variability of in vivo chlorophyll fluorescence (CF) per unit of chlorophyll concentration (CC) is analyzed using a biophysical model to improve the accuracy of CC assessments. Field measurements of CF and photosystem II (PSII) photochemical yield (PY) with the Advanced Laser Fluorometer (ALF) in the Delaware and Chesapeake Bays are analyzed vs. high-performance liquid chromatography (HPLC) CC retrievals. It is shown that isolation from ambient light, PSII saturating excitation, optimized phytoplankton exposure to excitation, and phytoplankton dark adaptation may provide accurate in vivo CC fluorescence measurements (R2 = 0.90–0.95 vs. HPLC retrievals). For in situ or flow-through measurements that do not allow for dark adaptation, concurrent PY measurements can be used to adjust for CF non-photochemical quenching (NPQ) and improve the accuracy of CC fluorescence assessments. Field evaluation has shown the NPQ-invariance of CF/PY and CF(PY−1-1) parameters and their high correlation with HPLC CC retrievals (R2 = 0.74–0.96), while the NPQ-affected CF measurements correlated poorly with CC (R2 = −0.22).Optics, Remote sensing, Biological oceanographyac2709, mh3170Lamont-Doherty Earth ObservatoryArticlesDetection and correction of inclination shallowing in deep sea sediments using the anisotropy of anhysteretic remanencehttps://academiccommons.columbia.edu/catalog/ac:143992
Collombat, Helene; Rochette, Pierre; Kent, Dennis V.http://hdl.handle.net/10022/AC:P:12403Mon, 30 Jan 2012 16:03:44 +0000Paleomagnetic data from recent Pleistocene to recent deep sea sediments from the continental rise of eastern North America exhibit a cyclical inclination shallowing, up to 30Â° with respect to the geocentric axial dipole value. This shallowing is strongly correlated with a ratio of anhysteretic remanent magnetization (ARM) anisotropy determined from a four position ARM anisotropy method. It is therefore proving that inclination variations in these cores are not due to paleosecular variation but in part to a bias in the remanence recording processes linked to depositional anisotropy. This study suggests that ARM anisotropy could provide a method to identify and correct for inclination shallowing in natural sediments.Sedimentary geology, Remote sensingdvk2Lamont-Doherty Earth ObservatoryArticlesUse of Remote Sensing for Monitoring Climate Variability for Integrated Early Warning Systems: Applications for Human Diseases and Desert Locust Managementhttps://academiccommons.columbia.edu/catalog/ac:126840
Ceccato, Pietro N.; Bell, Michael A.; Blumenthal, Martin Benno; Connor, Stephen J.; Dinku, Tufa; Grover-Kopec, Emily K.; Ropelewski, Chester F.; Thomson, Madeleine C.http://hdl.handle.net/10022/AC:P:9041Tue, 22 Jun 2010 16:33:19 +0000A number of the major human infectious diseases (like malaria and dengue) and Desert Locusts that still plague the developing world are sensitive to inter-seasonal and inter-decadal changes in environment and climate. Monitoring variations in environmental conditions such as rainfall and vegetation helps decision-makers at Ministries of Agriculture and Ministries of Health to assess the risk levels of Desert Locust outbreaks or malaria epidemics. The International research institute for climate and society (IRI) has developed products based on remotely sensed data to monitor those changes and provide the information directly to the decision-makers. This paper presents recent developments which use remote sensing to monitor climate variability, environmental conditions and their impacts on the dynamics of infectious diseases (malaria) and Desert Locust outbreaks.Remote sensing, Environmental studies, Epidemiologypnc2102, mab2010, mbb1, sjc2021, td2175, cfr30, mct2003International Research Institute for Climate and Society, Earth InstituteArticlesEnvironmental Data and Surveillancehttps://academiccommons.columbia.edu/catalog/ac:126834
Ceccato, Pietro N.; Bell, Michael A.; Blumenthal, Martin Benno; Connor, Stephen J.; Omumbo, Judith A.; Thomson, Madeleine C.; Trzaska, Sylwia A.http://hdl.handle.net/10022/AC:P:9039Tue, 22 Jun 2010 15:57:46 +0000An overview of the IRI Data Library.Environmental studies, Remote sensingpnc2102, mab2010, mbb1, sjc2021, jao2116, mct2003, sat2101International Research Institute for Climate and Society, Computer SciencePresentations